Main
Sabbir Ahmed Hemo
Statistician with a demonstrated history of working in the research for both industry and non-profit organizations. Skilled in R, Shiny, Statistical Data Analysis, SQL and Machine Learning.
Currently searching for a data science position that allows me to build tools using visualization and machine learning to help people explore and understand their data.
Education
MS, Applied Statistics
University of Dhaka
Dhaka, BD
2020 - 2019
- Thesis: Performance of Inverse Probability Weighting Compared to Multiple Imputation for Missing Binary Outcomes in Cluster Randomized Trials
BS, Applied Statistics
University of Dhaka
Dhaka, BD
2018 - 2015
- Project: Predicting malnutrition status of under-five children using tree based models
Industry Experience
Consultant Statistician
Grasp Industries Bangladesh
Dhaka, BD
2019
- Developed ODK Aggregate Server in a host server to collect data
- Formulate digital form on COLLECT Android App for collecting data
- Created a web dashboard to see real time insights from the data collected
Statistician
Participation Promoters Bangladesh Limited
Dhaka, BD
2019 - 2018
- Analyzed data in the baseline survey of nutrition project of CDP
- Designed the midline survey, analyzed collected data
- Wrote report based on the findings from the data
Volunteer Experience
Member
United Nations Youth Advisory Panel in Bangladesh
Dhaka, BD
2019 - 2014
- Worked as a technical advisor for UN agencies in Bangladesh
- Did different kind of surveys and FGDs
- Helped to organize different training session and workshop
Central Youth Volunteer
Save the Children in Bangladesh
Dhaka, BD
2015
- Support NCTF program with technical assistance
- Did interviews and FGDs for the baseline survey of WASH project
- Organized different training session and workshop
Speaker
Child Parliament
Bangladesh
2015 - 2013
- Lead the core committee of CP to arrange a session
- Facilitated different workshop and training sessions for Child Parliament
Selected Publications, Posters, and Talks
Predicting malnutrition status of under-five children using tree based models
Accepted as poster presentation at ICHPS 2020
San Diego, CA, USA
2019
- Authored with Prof. Md. Israt Rayhan
Performance of Inverse Probability Weighting Compared to Multiple Imputation for Missing Binary Outcomes in Cluster Randomized Trials
Proposed
N/A
2019